An Effective-Medium Tight-Binding Model for Silicon

A new method for calculating the total energy of Si systems is presented. The method is based on the effective-medium theory concept of a reference system. Instead of calculating the energy of an atom in the system of interest a reference system is introduced where the local surroundings are similar. The energy of the reference system can be calculated selfconsistently once and for all while the energy difference to the reference system can be obtained approximately. We propose to calculate it using the tight-binding LMTO scheme with the Atomic-Sphere Approximation(ASA) for the potential, and by using the ASA with charge-conserving spheres we are able to treat open system without introducing empty spheres. All steps in the calculational method is {\em ab initio} in the sense that all quantities entering are calculated from first principles without any fitting to experiment. A complete and detailed description of the method is given together with test calculations of the energies of phonons, elastic constants, different structures, surfaces and surface reconstructions. We compare the results to calculations using an empirical tight-binding scheme.Comment: 26 pages (11 uuencoded Postscript figures appended), LaTeX, CAMP-090594-

Direct pathway for sticking/desorption of H2 on Si(100)

The energetics of H2 interacting with the Si(100) surface is studied by means of ab initio total energy calculations within the framework of density functional theory. We find a direct desorption pathway from the mono-hydride phase which is compatible with experimental activation energies and demonstrate the importance of substrate relaxation for this process. Both the transition state configuration and barrier height depend crucially on the degree of buckling of the Si dimers on the Si(100) surface. The adsorption barrier height on the clean surface is governed by the buckling via its influence on the surface electronic structure. We discuss the consequences of this coupling for adsorption experiments and the relation between adsorption and desorption.

Bacterial attachment to uro-epithelial cells : mechanisms and consequences.

Microbial attachment to mucosal surfaces is a first step in mucosal infection. Specific interactions between microbial surface ligands and host receptors influence the distribution of microbes in their sites of infection. Adhesion has often been regarded as a sufficient end point, explaining tissue tropism and bacterial persistence at mucosal sites. Adherence, however, is also a virulence factor through which microbes gain access to host tissues, upset the integrity of the mucosal barrier, and cause disease. The induction of mucosal inflammation is one aspect of this process. Bacterial attachment to mucosal surfaces activates the production of pro-inflammatory cytokines that cause both local and systemic inflammation. Epithelial cells are one source of these cytokines. The binding of fimbrial lectins to epithelial cell receptors triggers transmembrane signaling events that upregulate cytokine-specific mRNA and increase cytokine secretion. P fimbriae that bind the globoseries of glycolipids cause the release of ceramides and activation of the ceramide signaling pathway which contributes to the IL-6 response. Spread of cytokines and other pro-inflammatory mediators from the local site contributes to the symptoms and signs of infection

Clonal Relationships among Shigella Serotypes Suggested by Cryptic Flagellin Gene Polymorphism

The presence of cryptic fliC alleles in the genomes of 120 strains representative of the four Shigella species was investigated. One fragment was obtained by PCR amplification of fliC, with a size varying from 1.2 to 3.2 kbp, depending on the species or serotype. After digestion with endonuclease HhaI, the number of fragments in patterns varied from three to nine, with sizes of between 115 and 1,020 bp. Patterns sharing most of their bands were grouped to constitute an F type. A total of 17 different F types were obtained from all strains included in this study. A unique pattern was observed for each the following serotypes: Shigella dysenteriae 1, 2, 8, and 10 and S. boydii 7, 13, 15, 16, and 17. On the contrary, S. dysenteriae serotype 13 and S. sonnei biotype e were each subdivided into two different F types. S. flexneri serotypes 3a and X could be distinguished from the cluster containing S. flexneri serotypes 1 to 5 and Y. S. flexneri serotype 6 clustered with S. boydii serotypes 1, 2, 3, 4, 6, 8, 10, 11, 14, and 18 and S. dysenteriae serotypes 4, 5, 6, 7, 9, 11, and 12. Two other clusters were outlined: one comprising S. dysenteriae serotypes 3, 12, 13 (strain CDC598-77), 14, and 15 and the other one joining S. boydii serotypes 5 and 9. None of the 17 fliC patterns was found in the fliC HhaI pattern database previously described for Escherichia coli. Overall, this work supports the hypothesis that Shigella evolved from different ancestral strains of E. coli. Moreover, the method outlined here is a promising tool for the identification of some clinically important Shigella strains as well as for confirmation of atypical isolates as Shigella spp